The Severe HAil Verification Experiment (SHAVE 2006) Or “What we did on our summer vacation” Travis Smith, OU / CIMMS / NSSL

The SHAVE team Operations Coordinator: Kiel Ortega Data collection team: Chad Echols, Angelyn Kolodziej, Chip Legett, James Miller, Christa Riley, Rachael Sigler NSSL/CIMMS scientists: Don Burgess, Kevin Manross, Kevin Scharfenberg, Travis Smith, Arthur Witt IT support: Karen Cooper and NSSL ITS

Motivation Big hail  lots of damage to things (some preventable) US Hail climatologic data is extremely poor – Storm Data – Not useful for “ground truth” of scientific applications: Wrong temporal / spatial scale (1 hour / 1 county) Not independent of the NWS warning process

Primary objective collect high temporal and spatial resolution* data that describe the distribution of hail sizes in hail swaths produced by thunderstorms * ~1 km by ~5 minutes

Developments that make this study possible WDSSII (experimental severe weather applications) run on CONUS GIS combined with weather data (Google Earth): – Internet databases of publicly available information about phone numbers and addresses “Manual” address/phone number collection

County directories for the Central / Northern Plains “Manual” address/phone number collection

The general idea Look at the national radar products in WDSSII – Max Expected Hail Size – Reflectivity, storm structure, 3-body scattering Call someone and ask them non-leading questions about the hail – Post-event – But very soon (minutes) after storm passage, lest they forget Good job for OU Meteorology students!

NOAA Hazardous Weather Testbed at 1313 Halley Circle (pre-NWC)

“Operations Coordinator” position selecting storms and hail swath cross- sections for interrogation

Data collection team: examine area selected by coordinator for calling “targets” conduct real-time surveys

Survey script (abridged) Identify self (NSSL) Estimate maximum and average hail size compared to coin or ball. What percentage of the ground is covered? “How long ago did it start and how long did it last?” If safe, ask them to measure a stone (if not melted). Thank them.

SHAVE reports versus Storm Data

Call results Data collection days 83 Busy / intercept operator 777 Total phone calls13854 Wrong location 47 “Good” data points4880 No answer or machine 5485 “Good” except time658 Disconnected / Do Not Call 1286 Hail w/ questionable location 42 Other307 Hail w/ questionable size 371

How good are the hail size estimates?

Hail size distribution for “good” data points

Summary Hail reports collected by NWS during SHAVE period across the continental US: – 5532 – 20 credited to SHAVE Hail reports (severe, non-severe, null) collected by SHAVE on select storms: – 5538 – 1827 “severe” reports (> ¾”)

What’s next? Analyze lots of data! SHAVE 2007? – Expand to include damaging winds and tornadoes – Digital photos of damage, post-event surveys Improvements to existing hail detection applications Probabilistic warning applications SHAVE 2008 or 2009: polarimetric data

Fun with Phones Them: “Did it hail? Hail, yes!” Us: “Did you get any damage from the winds?” Them: “Are you going to pay for it? If so, YES!” "You bet it's hailing! Wait, am I on TV?" -some guy in Michigan

Fun with phones Them, to someone else on the other end: “Hey, did we get any hail? Someone from The Weather Channel is on the phone.”

Other possible names for this presentation Virtual storm chasing with Google Earth Trapped all summer in a small room with no windows and no thermostat! ‘Hello, this is the…’ -- An adventure in collecting severe weather reports from the public. Pea, butterbean, eye ball, hen egg, tea cup… what size is your hail?

The End Thanks to Rick Smith, Alan Stewart, Jennifer Palucki and many others for their comments on the data collection survey script and project plan. Special thanks (again!) to the data collection team! Visit for live experimental data in Google Earthhttp://wdssii.nssl.noaa.gov Contact: